Predicting and evaluating different pretreatment methods on methane production from sludge anaerobic digestion via automated machine learning with ensembled …

X Cheng, R Xu, Y Wu, B Tang, Y Luo… - ACS ES&T …, 2023 - ACS Publications
Accurate prediction of methane production in anaerobic digestion with various pretreatment
strategies is of the utmost importance for efficient sludge treatment and resource recovery …

Integrating automated machine learning and metabolic reprogramming for the identification of microplastic in soil: A case study on soybean

Z Liu, W Wang, Y Geng, Y Zhang, X Gao, J Xu… - Journal of Hazardous …, 2024 - Elsevier
The accumulation of polyethylene microplastic (PE-MPs) in soil can significantly impact plant
quality and yield, as well as affect human health and food chain cycles. Therefore …

Phenotyping of Drought-Stressed Poplar Saplings Using Exemplar-Based Data Generation and Leaf-Level Structural Analysis

L Zhou, H Zhang, L Bian, Y Tian, H Zhou - Plant Phenomics, 2024 - spj.science.org
Drought stress is one of the main threats to poplar plant growth and has a negative impact
on plant yield. Currently, high-throughput plant phenotyping has been widely studied as a …

Quantitative analysis of lateral root development with time-lapse imaging and deep neural network

Y Uemura, H Tsukagoshi - Quantitative Plant Biology, 2024 - cambridge.org
During lateral root (LR) development, morphological alteration of the developing single LR
primordium occurs continuously. Precise observation of this continuous alteration is …

Decrypting the complex phenotyping traits of plants by machine learning

J Zdrazil, L Kong, P Klimes, FI Jasso-Robles… - bioRxiv, 2024 - biorxiv.org
Phenotypes, defining an organism's behaviour and physical attributes, arise from the
complex, dynamic interplay of genetics, development, and environment, whose interactions …